WO2019069994A1

WO2019069994A1 - Airflow measuring device

Info

Publication number: WO2019069994A1
Application number: PCT/JP2018/037079
Authority: WO
Inventors: 宮崎　憲一; 山下　秀一; ヘーガンネーサン; 大谷　幸利
Original assignee: 株式会社デンソー; 国立大学法人宇都宮大学
Priority date: 2017-10-03
Filing date: 2018-10-03
Publication date: 2019-04-11
Also published as: JP7006104B2; JP2019066384A

Abstract

An amount of change in temperature (ΔT) of a surface (10a) of an object (10) over a very short time is calculated, and the amount of change in temperature (ΔT) is made visible. Since airflow at the surface (10a) of the object (10) can be made visible in this way, it is not necessary to heat the object (10), and measurements can even be taken outdoors, for example, and there are therefore no restrictions on the measuring location. Further, real-time airflow measurement is also possible. It is therefore possible to provide an airflow visualizing device with which there are no restrictions on the object to be measured or the measurement location, and with which real-time airflow measurement can be performed.

Description

Airflow measuring device

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based on Japanese Patent Application No. 2017-193645 filed on October 3, 2017, the contents of which are incorporated herein by reference.

The present disclosure relates to an air flow measurement device capable of measuring an air flow on the surface of an object, and is suitably applied to, for example, an air flow visualization device capable of measuring by visualizing an air flow on the surface of an object.

DESCRIPTION OF RELATED ART Conventionally, in patent document 1, the visualization apparatus which can visualize the airflow on the surface of an object is proposed as an airflow measurement apparatus. In this device, the air flow is visualized by heating the object whose flow is to be visualized and then measuring the temperature change of the heated object due to the wind. Specifically, this device measures the temperature distribution of the heated object using a thermoviewer based on the fact that the temperature of the object surface decreases as the wind hits the heated object at a greater place, and the temperature distribution is Visualization of the air flow to the heating object is performed.

Japanese Patent Application Laid-Open No. 63-27766

However, the visualization device of Patent Document 1 described above can not visualize the air volume to the object without heating the object. For this reason, it is necessary to be an object that can be heated, a place, for example, a human body can not be measured, and an outdoor where a heating device can not be placed can not be measured. It is limited. In addition, it is difficult to measure airflow in real time because of using temperature change over a long time.

In view of the above-described point, the present disclosure aims to provide an air flow measurement device that is not limited in measurement object and measurement location, and can also perform air flow measurement in real time.

One aspect of the present disclosure is an air flow measurement device that performs measurement on the surface of an object, and a camera that acquires measurement data of the surface at a predetermined frame rate as emission light data of the surface, and measurement acquired by the camera Temperature change calculated by the change amount calculation unit, which calculates the temperature change amount that is the difference between the reference temperature for each pixel or each pixel of each frame and the temperature at the time of temperature change based on the data The measurement data creation unit has a measurement data creation unit that creates time change data of the temperature change amount using difference data between the reference temperature and the temperature at the time of the temperature change according to the magnitude of the amount. Calculate time change data.

Thus, based on the measurement data of the surface of the object, the amount of temperature change which is the difference between the reference temperature for each pixel or each pixel of each frame and the temperature at the time of temperature change, ie, the minute time on the surface of the object The amount of temperature change is calculated and the amount of temperature change is measured. In this way, since the air flow on the surface of the object can be measured, it is not necessary to heat the object, and measurement can be performed outdoors as well, so there is no restriction on the measurement location. It also enables real-time air flow measurement. Therefore, the measurement object and the measurement place are not limited, and it is possible to obtain an air flow measurement device capable of performing air flow measurement in real time.
In addition, the parenthesized reference symbol attached to each component etc. shows an example of the correspondence of the component etc. and the specific component etc. as described in the embodiment to be described later.

It is a figure which shows the block configuration of the airflow visualization device concerning 1st Embodiment. It is the chart which showed the specification of the camera with which an airflow visualization device is equipped. It is the graph which showed the relationship between environmental temperature and temperature resolution (NETD: Noise Equivalent Temperature Difference). It is a flowchart of the process which the computer of air flow visualization apparatus performs. It is the figure which showed a mode when disorder generate | occur | produced in the airflow on the surface of an object. It is the figure which showed a mode that the temperature change of the object surface produced by disorder to air flow. It is the figure which showed a mode when the airflow on the surface of an object stabilized again. FIG. 5 is a view showing the change of the surface temperature of the object in the process of FIG. 4A to FIG. 4C. It is the figure which showed the mode of the change of the temperature of an object surface, and the difference of the temperature of an object surface instantaneously. It is a figure explaining an estimation method of direction and speed of a field which moves between consecutive frames. It is the figure which showed the relationship between the movement distance in a flame | frame, and the air volume of the airflow in the object surface. It is the figure which showed a mode when an airflow vector was shown by the arrow with the image data which visualized temperature variation.

Hereinafter, embodiments of the present disclosure will be described based on the drawings. In the following embodiments, parts that are the same as or equivalent to each other will be described with the same reference numerals.

First Embodiment
An air flow visualization device according to the present embodiment will be described. The air flow visualization device of the present embodiment is for visualizing the air flow on the surface of an object, and has, for example, a system configuration shown in FIG.

As shown in FIG. 1, the air flow visualization device is configured to have a camera 1, a computer 2, and a display 3.

The camera 1 is configured of, for example, an infrared camera. The camera 1 inputs an image of each pixel with, for example, one pixel as a minimum unit, and transmits the video signal, that is, image data to be measurement data to the computer 2.

Although the specification of the camera 1 is arbitrary, here, for example, an infrared camera of the specification shown in FIG. 2A is used. Specifically, the detector is InSb, the number of pixels is 640 × 512, the pixel pitch is 20 μm, the detection wavelength band is 2.95-4.97 μm, the F value, that is, the size of the lens of the camera 1 is f / 2.3. Using a quantum-type cooled infrared camera with an operating temperature of 77 K and a frame rate of 60 Hz. Then, by performing averaging processing for four frames, display is made at 15 Hz. Besides, there is no problem even if a so-called uncooled infrared camera such as a thermopile using the Seebeck effect, a bolometer type using resistance change, or a pyroelectric type using pyroelectric effect is used.

Further, in order to detect a minute temperature variation, it is important to be able to distinguish between the temperature of the object 10 and the NETD of the camera 1, that is, to what extent the temperature difference can be distinguished. In the present embodiment, as the camera 1, the relationship between the ambient temperature around the object 10 and the NETD has the relationship shown in FIG. 2B.

The computer 2 performs image processing based on image data input from the camera 1 and plays a role of creating data in which the air flow is visualized. Further, the computer 2 performs calculation of an air flow vector corresponding to the air volume and direction of the air flow from the image data after creation, and plays a role of transmitting the calculation result of the image data and air flow vector after creation to the display 3. The specific operation of the computer 2 will be described later.

The display 3 constitutes an image display unit, and displays the calculation result of the image data and the air flow vector transmitted from the computer 2 as an image. Thus, the amount of temperature change of the object surface in a minute time can be represented as an image, and an airflow vector can be shown in the image.

As described above, the air flow visualization device according to the present embodiment is configured. Subsequently, the operation of the air flow visualization device configured as described above will be described with reference to the flowchart of the process executed by the computer 2 shown in FIG. 3.

In the airflow visualization device, the camera 1 captures an image of the surface 10a of the object 10 to acquire image data of the surface 10a, and inputs the data to the computer 2 to cause the computer 2 to perform various processes. An operation of displaying the processing result on the display 3 is performed.

When the image data is input, the computer 2 performs image processing based on the image data to create data in which the air flow is visualized. The image data is data of radiation of the surface 10 a of the object 10. Since the radiation of the surface 10a is output according to the temperature of the surface 10a, the air flow of the surface 10a can be visualized by processing the image data, that is, the data of the radiation. Further, the computer 2 performs an optical flow analysis of the image data after creation to calculate an air flow vector. Then, the computer 2 transmits the calculated image data and the calculation result of the airflow vector to the display 3.

Specifically, the computer 2 performs the above operation by executing the process shown in the flowchart of FIG.

First, as shown in step S100 of FIG. 3, the computer 2 inputs an infrared image as image data from the camera 1. Next, the process proceeds to step S110 to calculate an average temperature in a frame of each input image. In this average temperature calculation, an average value of temperatures per pixel in a plurality of frames is calculated. Subsequently, in step S120, the temperature change amount ΔT with respect to the reference temperature in a minute time is calculated based on the result of the average temperature calculation in step S110 for visualization. Further, in step S130, image data for visualization is created based on the calculation result of the temperature change amount ΔT with respect to the reference temperature in a minute time, and in step S140, optical flow analysis is performed as calculation of the air flow vector. Then, in step S150, the image data obtained in step S130 and the calculation result of the air flow vector in step S140 are transmitted to the display 3 to display the amount of temperature change of the object surface in a minute time or Visualize the airflow vector.

Specifically, in step S110, calculation with narrow time and calculation with wide time longer than that are performed as average temperature calculation. In the average temperature calculation in a narrow time, a moving average value of the temperature for each pixel in a first predetermined number of frames corresponding to a predetermined short time, for example, four frames is calculated. With this narrow time average temperature calculation, the temperature after fluctuation in minute time is calculated. In addition, in the average temperature calculation in the wide time, the movement of the temperature for each pixel in the second predetermined number corresponding to the wide time longer than the narrow time, that is, several minutes more than the first predetermined number, for example 80 frames The average value is calculated. The reference temperature is calculated by the average temperature calculation in the wide time. By performing the average temperature calculation in such a wide time, it is possible to average the temperature variation due to the disturbance factor and to obtain the time variation temperature average that facilitates the extraction of the minute temperature variation.

The temperature of the object surface changes by a mechanism as shown in FIGS. 4A to 4C.

First, as shown in FIG. 4A, a laminar flow 11 flows as a gas flow along the surface 10 a of the object 10 in the object 10. At the boundary between the laminar flow 11 and the object 10, a boundary layer 12 which is a stable layer is formed. The boundary layer 12 is, for example, in a state of being spread by the vortices 12 a interspersed innumerably on the surface 10 a of the object 10.

However, although the laminar flow 11 flows along the surface 10 a of the object 10, the flow direction is not necessarily constant. For this reason, as shown in FIG. 4A, disturbance 13 from the laminar flow 11 toward the boundary layer 12 may occur. Due to the disturbance of the laminar flow 11 due to the disturbance 13, as shown in FIG. 4B, a part of the vortex 12a of the boundary layer 12 which is a stable layer is peeled off. Then, in the region where the vortex 12a is peeled off, the temperature of the surface 10a is changed, and the temperature is lower than that of the other region of the surface 10a.

Subsequently, as shown in FIG. 4C, the boundary layer 12 is stabilized again and returns to the state in which it is spread by the vortex 12a.

The temperature change in these states is represented as shown in FIG. That is, when states (1) to (3) are shown in FIGS. 4A to 4C, respectively, as shown in FIG. 5, the temperature is substantially constant in the state (1) and in the state (2). When the temperature is low, the temperature rises again to the state (1). The time when the temperature change occurs at this time is, for example, a minute time of several seconds, and the temperature change amount can be represented by ΔT.

As described above, since the temperature change of the surface 10 a of the object 10 in a minute time indicates the change of the air flow, the change of the air flow is obtained by obtaining the temperature change amount ΔT in step S120.

Here, the temperature change amount ΔT in a minute time is an instantaneous temperature change that occurs in a few seconds. Therefore, the temperature change amount ΔT can be calculated by subtracting the temperature at the time of the temperature change from the reference temperature, that is, the temperature before the temperature change. For example, since the temperature of the object surface and the time change of the temperature fluctuation are represented as a graph as shown in FIG. 6, it is possible to calculate the difference of the temperature of the object surface instantaneously as shown in FIG. it can. And, basically, as shown in the figure, the change in instantaneous time in the difference of the temperature of the object surface becomes the temperature change amount ΔT. However, even when a noise-like image change occurs in the image of the camera 1, it may appear as a temperature change. In addition, since the temperature of the surface 10 a of the object 10 changes gradually, it is preferable to exclude the influence of the gradual temperature change.

For this reason, in step S110, a temperature average value in a wide time is obtained by the average temperature calculation as the reference temperature, in other words, the temperature before the temperature change, so that the influence of the gradual temperature change can be excluded. Further, as a temperature at the time of temperature change, a temperature average value in a narrow time is obtained by the average temperature calculation so as to suppress a decrease in accuracy when a noise-like image change occurs.

Specifically, for each pixel, moving average value MovingAvg80 {T (t)} of 80 frames 'worth of temperature is calculated as wide-time mean temperature calculation, and temperature of 4 frames' worth as narrow-time average temperature calculation. The moving average value of MovingAvg4 {T (t)} is calculated. Then, in step S120, the temperature change amount ΔT (t) is obtained as the difference between the temperature average value of the wide time and the temperature average value of the narrow time, as shown in the following equation. In the following equations, MovingAvg80 {T (t)} and MovingAvg4 {T (t)} are further simplified and used as equations expressed as M80 (t) and M4 (t), respectively.

(1)
ΔT (t) = MovingAvg80 {T (t)}-MovingAvg4 {T (t)}
= M80 (t)-M4 (t)
Thus, the temperature change amount ΔT can be acquired. Therefore, in step S130, the time change data of the temperature change ΔT using the image of the temperature change ΔT obtained from the result of the average temperature calculation for each pixel, that is, the difference data of the reference temperature and the temperature at the time of the temperature change. Create image data representing the image. For example, the brightness of gray scale is changed in accordance with the temperature change amount ΔT for each pixel, and image data is created such that the larger the temperature change amount ΔT, the brighter the display.

At this time, it is preferable to display the image as black or white for an area where | ΔT (t) | ≧ X (where X is an arbitrary value) in the creation of the image data. This is to remove the temperature change amount ΔT (t) obtained as a large absolute value in terms of noise, and is a method of processing a singular point. This enables depiction in the range of | ΔT (t) | <X in all regions in the frame shown in the image data.

Further, as described above, the region where the vortex 12a is peeled is moved according to the volume and direction of the airflow, that is, the vector of the airflow. For this reason, the vector of air flow can be estimated by performing calculation based on the image data created as time change data. Specifically, the temperature change amount ΔT (t) obtained from the average temperature calculation result for each pixel is input, and the optical flow analysis is performed from there to determine the movement distance between the frames of the region where the vortex 12a is peeled off. If analyzed, the airflow vector can be estimated. Therefore, in step S140, optical flow analysis is performed as calculation of the airflow vector.

Various well-known techniques can be applied to optical flow analysis, and for example, a general Lucas-Kanade method can be used as optical flow analysis. The Lucas-Kanade method is a method of estimating the direction and velocity of a moving area, for example, in an arbitrary frame and the next frame. For example, as shown in FIG. 7, an arbitrary frame is frame 1 and the next frame is frame 2. Then, the moving distance from the center of gravity of the region R1 in which the temperature change occurs in the frame 1 to the center of gravity of the region R2 in which the temperature change occurs in the frame 2; The movement distance and direction between the centers of gravity of the tracked area R1 and the area R2 are vectors corresponding to the volume and direction of the air flow. For example, the moving distance between the centers of gravity of the region R1 and the region R2 and the air volume of the air flow on the object surface are expressed as a relationship as shown in FIG.

The actual air flow velocity can be calculated by multiplying the distance per pixel. Specifically, when imaging is performed by the camera 1, the range of the imaging target in one frame is determined according to the distance from the camera 1 to the imaging target. For example, it is assumed that an actual imaging range in one frame, that is, an actual distance in one direction of an image reflected in one frame is L1 mm. In that case, as shown in FIG. 2A, when the number of pixels in the left-right direction of the camera 1 is 640, L1 / 640 [mm] is the shooting distance per pixel. For this reason, the velocity of the air flow can be obtained by multiplying L1 / 640 [mm] by the moving distance between the centers of gravity of the regions R1 and R2 in each frame, that is, the number of moving pixels.

However, the velocity of the air flow described here is the velocity at the imaging interval of the frame, in other words, the velocity for the time of the imaging cycle. The imaging interval of a frame is represented by a frame rate, and as shown in FIG. 2A, in the present embodiment, the frame rate is 15 Hz. For this reason, when expressing the velocity of the air flow as a second velocity, the above-mentioned L1 / 640 [mm] is multiplied by the frame rate.

Therefore, if L1 is 3 × 640, that is, if the movement amount between the centers of gravity of region R1 and region R2 in each frame is 16 pixels / frame, and the frame rate is 15 Hz, It can be asked.

(2)
Second speed of air flow = (width in left / right mm in one frame / number of pixels in one frame) x (amount of movement between centers of gravity in each frame) x (frame rate / s)
= 3 mm / pixel x 16 pixels / frame x 15 frames / s
= 0.7
Thus, when image data of the temperature change amount ΔT is created and optical flow analysis is performed as calculation of the airflow vector, the created image data and the result of the optical flow analysis are transmitted to the display 3 in step S150. . As a result, the airflow vector is displayed on the display 3 so as to overlap with or separately from the image data of the temperature change amount ΔT, and these visualizations are performed. For example, as shown in FIG. 9, the temperature change amount ΔT is indicated by light and shade, and the airflow vector is displayed by an arrow to perform visualization.

As described above, in the airflow visualization device of the present embodiment, the temperature change amount ΔT in a minute time of the surface 10 a of the object 10 is calculated, and the temperature change amount ΔT is visualized. In this manner, since the air flow on the surface 10 a of the object 10 can be visualized, the object 10 does not have to be heated, and measurement can be performed outdoors or the like, and there is no restriction on the measurement location. It also enables real-time air flow measurement. Therefore, it is possible to provide an airflow visualization device capable of performing airflow measurement in real time without being limited in the measurement object or the measurement location.

Furthermore, by visualizing the air flow vector by arrow display or the like, it is possible to visualize the air volume and direction of the air flow, and air flow monitoring can be performed more accurately.

Such an air flow visualization device can be applied to the visualization of air flow with respect to various measurement objects, and in particular, at a medium distance, for example 10 m to 100 m, in which the air flow can not be visualized conventionally. It can be used to visualize air flow. For example, applicable applications include air volume control and air flow management of an air conditioner by air flow visualization in a room or in a vehicle cabin, outdoor air flow monitoring, and air resistance optimization by air flow and turbulence visualization.

(Other embodiments)
The present disclosure has been described based on the above-described embodiment, but is not limited to the embodiment, and includes various modifications and variations within the equivalent range. In addition, various combinations and forms, and further, other combinations and forms including only one element, or more or less than these elements are also within the scope and the scope of the present disclosure.

For example, although the above embodiment has described the case of applying the method of changing the light and shade of gray scale according to the magnitude of the temperature change amount ΔT in a minute time as the air flow visualization method, other methods are applied. You can also. For example, the color may be changed in accordance with the magnitude of the temperature change amount ΔT.

Further, by controlling the wavelength of light input by the camera 1, it is also possible to visualize a specific air flow. For example, while enabling the camera 1 to input an infrared image, the filter 1a is installed in the camera 1 as shown in FIG. 1, and the image data filtering process is performed. Thereby, it is also possible to visualize the airflow by specifying a specific airflow, for example, toxic gas or carbon dioxide, and measuring the temperature. In the case of toxic gas, the wavelength of light to be extracted varies depending on the type of gas. For this reason, although the wavelength which the filter 1a passes according to it will be set, for example, when performing airflow of carbon dioxide, if the filter 1a should be able to pass 4.26 micrometers and the wavelength of that vicinity good.

Further, in the above embodiment, as visualization of the air flow, in addition to visualization of the temperature change amount ΔT, visualization of the air flow vector is also described simultaneously. However, at least the temperature change amount ΔT is visualized. You can visualize the air flow.

Further, in the above embodiment, calculation of the number of moving pixels of the center of gravity between the region R1 and the region R2 in which the temperature change amount ΔT and the temperature change occur in each pixel is performed. However, this is just an example. For example, assuming a plurality of adjacent pixels in each frame, for example, 4 pixels of 2 × 2 as one section, the temperature change amount ΔT or the number of movement sections of the center of gravity of the area R1 and the area R2 The calculation may be performed.

In the above embodiment, the computer 2 calculates the average temperature in the narrow time or the wide time, calculates the temperature change ΔT, calculates the temperature change ΔT, and changes the image data in visualization etc. A measurement data creation unit that creates data and a vector calculation unit that calculates an airflow vector are configured. However, this is only an example. For example, each component may be configured by a different computer. In addition, in the vehicle, various controls related to the vehicle are performed by various electronic control devices (hereinafter referred to as ECUs), but each component may be configured by one or more of the ECUs.

Further, in the above embodiment, the airflow visualization device that can perform visualization of the airflow has been described as an example including the airflow measurement device, but the airflow measurement device has a function capable of measuring the airflow on at least the surface of the object. It is good if it is.

Claims

An air flow measuring device for measuring an air flow on a surface (10a) of an object (10), comprising:
A camera (1) for acquiring measurement data of the surface at a predetermined frame rate as data of radiation on the surface;
A change amount calculation unit that calculates a temperature change amount (ΔT) that is a difference between a reference temperature for each pixel or each pixel of each frame and a temperature at the time of temperature change based on the measurement data acquired by the camera 2, S110, S120),
According to the magnitude of the temperature change calculated by the change calculation unit, measurement is performed to create time change data of the temperature change using difference data between the reference temperature and the temperature at the time of the temperature change. A data creation unit (2, S130);
The air flow measuring device which calculates the said time change data which the said measurement data creation part created.
Calculating an average value of temperatures in a narrow time which is an average value of temperatures of the pixels or plural pixels in the first predetermined number of the frames, and calculating a second predetermined number more than the first predetermined number of the frames And an average value calculation unit (2, S110) for calculating an average value of temperatures in wide time which is an average value of temperatures of the pixels or a plurality of pixels in a few minutes.
The change amount calculation unit according to claim 1, wherein a value obtained by subtracting the average value of the temperatures in the narrow time period from the average value of the temperatures in the wide time period calculated by the average value calculation unit is the temperature change amount. Air flow measuring device.
The air flow measuring device according to claim 1 or 2, wherein the camera detects light having a wavelength of 2 to 14 μm.
The air flow measuring device according to any one of claims 1 to 3, wherein the camera includes a filter (1a) that transmits only light of a specific wavelength.
A vector for calculating an air flow vector corresponding to the air volume and direction of the air flow by performing optical flow analysis of a region where the temperature change occurs in the surface based on the time change data generated by the measurement data generation unit The air flow measuring device according to any one of claims 1 to 4, further comprising a calculation unit (2, S140).
A gas flow measuring device according to any one of claims 1 to 4, including:
A display unit (3) for displaying the measurement data as an image;
An airflow visualization device that visualizes the airflow by displaying an image of the measurement data on the display unit.
A vector for calculating an air flow vector corresponding to the air volume and direction of the air flow by performing optical flow analysis of a region where the temperature change occurs in the surface based on the time change data generated by the measurement data generation unit Has a calculation unit (2, S140),
The air flow visualization device according to claim 6, wherein the display unit displays the air flow vector calculated by the vector calculation unit in addition to the display of the time change data generated by the measurement data generation unit.
The air flow visualization device according to claim 7, wherein the vector calculation unit calculates the air flow vector by tracking the movement distance and the direction of the area between the respective frames.
The air flow visualization device according to claim 8, wherein the air flow vector is calculated by tracking the movement distance and the direction of the area for each section, with a plurality of adjacent pixels in each frame as one section.